vLLM

A fast and easy-to-use library for LLM inference and serving.

News

7.4.2026 vLLM now available as a separate module on Roihu-GPU

Available

Currently supported vLLM versions:

Version	Module	Notes
0.19.1	python-vllm/0.19.1	Default
0.18.0	python-vllm/0.18.0

Includes vLLM, PyTorch and related libraries with GPU support via CUDA/ROCm.

PyTorch vs vLLM

If you don't particularly need vLLM, we recommend using the full PyTorch module instead, which includes more packages.

If you find that some package is missing, you can often install it yourself using pip install. It is recommended to use Python virtual environments. See our Python documentation for more information on how to install packages yourself. If you think that some important package should be included in the module provided by CSC, please contact our servicedesk.

All modules are based on containers using Apptainer (previously known as Singularity). Wrapper scripts have been provided so that common commands such as python, python3, pip and pip3 should work as normal.

License

vLLM is covered by the Apache License 2.0.

Usage

To load the default version on Roihu-GPU:

module load python-vllm

If you wish to have a specific version (see above for available versions), use:

module load python-vllm/0.18.0

To check the exact packages and versions included in the loaded module you can run:

pip list

Example script for usage

See the vLLM section in CSC's Machine learning guide, which has links to example script for using vLLM on Roihu.

The full Machine learning guide might also be of use.

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